Unnecessary preoperative testing poses a risk to patient safety, causes surgical delays, and increases healthcare costs. We describe the effects of implementing a fully EHR-integrated closed-loop clinical decision support system (CDSS) for placing automatic…
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Generating realistic synthetic health data (e.g., electronic health records), holds promise for fundamental research, AI model development, and enhancing data privacy safeguards. Generative Adversarial Networks (GANs) have been employed for this purpose, but their…
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Autonomous artificial intelligence (AI) for pediatric diabetic retinal disease (DRD) screening has demonstrated safety, effectiveness, and the potential to enhance health equity and clinician productivity. We examined the cost-effectiveness of an autonomous AI strategy…
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In resource-constrained countries like India, mammography-based breast screening is challenging to implement. This state-wide study, funded by the Government of Punjab, evaluated the use of Thermalytix, a low-cost, radiation-free AI tool, for breast cancer…
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Deep learning analysis of electrocardiography (ECG) may predict cardiovascular outcomes. We present a novel multi-task deep learning model, the ECG-MACE, which predicts the one-year first-ever major adverse cardiovascular events (MACE) using 2,821,889 standard 12-lead…
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In emergency situations, timely contact with emergency medical communication centers (EMCCs) is critical for patient outcomes. Increasing call volumes and economic constraints are challenging many countries, necessitating organizational changes in EMCCs. This study uses…
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Nasal endoscopy is crucial for the early detection of nasopharyngeal carcinoma (NPC), but its accuracy relies heavily on the clinician’s expertise, posing challenges for primary healthcare providers. Here, we retrospectively analysed 39,340 nasal endoscopic…
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Due to the large size and lack of fine-grained annotation, Whole Slide Images (WSIs) analysis is commonly approached as a Multiple Instance Learning (MIL) problem. However, previous studies only learn from training data, posing…
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Patients with cirrhosis have high systemic inflammation (TNFα, CRP, and IL-6) that is associated with poor outcomes. These biomarkers need continuous non-invasive monitoring, which is difficult with blood. We studied the AWARE sweat-sensor to…
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Patient smart access and self-triage systems have been in development for decades. As of now, no LLM for processing self-reported patient data has been published by health systems. Many expert systems and computational models…
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